As the number of images available online continues to expand, image-based search engine mechanisms continue to pursue improved techniques that return the most relevant images in response to receiving a search query. Typically, search engines initially rely on matching textual information associated with an image (e.g., image titles, image captions, URLs, etc.) to the textual elements (e.g., keywords) provided in the search query. The initial textual matching identifies candidate images for the search query and ranks the identified candidate images according to a relevance score based on the textual matching.
However, the textual information fails to capture and/or consider the visual content of an image. Therefore, textual-based relevance ratings are susceptible to errors because the textual information associated with images often does not provide reliable image-based results to a search query.